Project on Type 2 diabetic and Hyperglycemic Pancreatic Islets

Introduction

Type 2 Diabetes (T2D) is a serious health concern and identifying gene markers associated with the disease can help catch it early in new patients.

Our analysis is focused on

  • Identifying gene markers

  • Identifying key over- and under-expressed genes

Looking into co-expression of key genes

Data source:

A Systems Genetics Approach Identifies Genes and Pathways for Type 2 Diabetes in Human Islets
(PMID: 22768844) (GEO ID: GDS4337)

Materials - Data Set Description

Data set overview:

  • 14481 different genes

  • 63 samples

    • 9 with T2D

    • 54 controls

Descriptive statistics:

  • Similar mean gene expression across groups

  • Overall low mean expression levels

  • Slightly right-skewed distribution

  • => Investigate significant difference of genes between the groups

Materials - Wrangling

Frederik

Methods - Median Expression Differences

Lena - Goal: Identify genes with largest expression differences between T2D and control

- Approach: - Compute median expression per gene for T2D and control samples - Calculate absolute differences between groups per gene

  • Visualization:
    • Plot 30 genes with the most different expressions
    • Bar plot and boxplots

Methods - p.value

  1. Transform data

  2. Pivot Longer

  3. Nest the Log Fold Changes

  4. Creating linear regression models for each gene

    • lm(log_fold_change ~ disease.state)

  5. Select genes from significant p-values

Bolette

Results - Median Expression Differences

Lena

::::: columns ::: column :::

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Results - p.value

  • Final p-value selection was p < 0.01
  • - 635 genes labelled significant
  • Top 30 most significant (lowest p-vals) chosen for visualisation

Results - combined / correlation matrix

Bolette

Discussion

1) Difference in two methods

2) Sum up which genes are found by the analysis

3) does they support the litterature? uniprot…

Conclusion